# Towards Grammatical Tagging for the Legal Language of Cybersecurity

arXiv: https://arxiv.org/abs/2306.17042 · HTML: https://mlsanity.com/paper/2306.17042/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 32 references that are in the map.
- First posted on arXiv 29 Jun 2023.

## Builds on (most cited first, 8 of 8)

- [JEC-QA: A Legal-Domain Question Answering Dataset](https://mlsanity.com/paper/1911.12011/) (2019)
- [LEGAL-BERT: The Muppets straight out of Law School](https://mlsanity.com/paper/2010.02559/) (2020)
- [Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey](https://mlsanity.com/paper/1711.04305/) (2017)
- [CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service](https://mlsanity.com/paper/1805.01217/) (2018)
- [Distinguish Confusing Law Articles for Legal Judgment Prediction](https://mlsanity.com/paper/2004.02557/) (2020)
- [Patent Claim Generation by Fine-Tuning OpenAI GPT-2](https://mlsanity.com/paper/1907.02052/) (2019)
- [Exploring the Use of Text Classification in the Legal Domain](https://mlsanity.com/paper/1710.09306/) (2017)
- [Predicting the Behavior of the Supreme Court of the United States: A General Approach](https://mlsanity.com/paper/1407.6333/) (2014)

## Built on by (most cited first, 1 of 1)

- [An automated method for the ontological representation of security directives](https://mlsanity.com/paper/2307.01211/) (2023)

## Abstract (arXiv)

Legal language can be understood as the language typically used by those engaged in the legal profession and, as such, it may come both in spoken or written form. Recent legislation on cybersecurity obviously uses legal language in writing, thus inheriting all its interpretative complications due to the typical abundance of cases and sub-cases as well as to the general richness in detail. This paper faces the challenge of the essential interpretation of the legal language of cybersecurity, namely of the extraction of the essential Parts of Speech (POS) from the legal documents concerning cybersecurity. The challenge is overcome by our methodology for POS tagging of legal language. It leverages state-of-the-art open-source tools for Natural Language Processing (NLP) as well as manual analysis to validate the outcomes of the tools. As a result, the methodology is automated and, arguably, general for any legal language following minor tailoring of the preprocessing step. It is demonstrated over the most relevant EU legislation on cybersecurity, namely on the NIS 2 directive, producing the first, albeit essential, structured interpretation of such a relevant document. Moreover, our findings indicate that tools such as SpaCy and ClausIE reach their limits over the legal language of the NIS 2.